The invention relates to the field of computerized social networking, and in particular to the problems of processing chat sessions and locating Subject Matter Experts (SMEs) within social networks.
Examples of expertise networks are known on the consumer web, and include message boards and online discussion forums focused on specialized topics. As members of online communities formed by these networks, participants can freely post questions as information seekers (users) and respond to questions as information providers (experts). Such knowledge sharing creates content on specialized topics that web search engines can then index to support similar information needs in the future which are otherwise hard to satisfy.
When social networks are used in a professional environment, one issue that presents itself is improving finding experts to enhance business operations. This issue arises more within larger organizations than smaller ones—and even more where organizations have multiple sites, especially where the sites are in more than one country. As organizations become increasingly global and telecommunications based, the geographical location of individual employees becomes less consequential in the daily conduct of business operations. By tapping into a global view of how people are connected in an organization, tools based on social network analysis can enhance long-range information-flow and knowledge sharing within the enterprise, beyond what can be offered by local access to other employees and traditional information sources such as intranet web pages.
A number of techniques have been proposed for finding experts in social networks. Generally, techniques for finding experts in social networks have involved matching a question with expert profiles, sometimes taking into account expert availability.
One example is to be found in J. Zhang et al., “Expertise Networks in Online Communities: Structure and Algorithms,” International World Wide Web Conferences Committee (IW3C2), (May 8-12, 207, Banff, ALberta, Canada; ACM 978-1-59593-65-7/07/0005 (“Zhang et al.”). Zhang et al. concluded that methods like page-rank that work for ranking web-pages, do not work very well for ranking experts due to structural differences in the web graph and the online user-expert network respectively. They simulated the dynamics of question-answering and found that expertise-networks are quite different structurally because users and experts do not behave in an identical manner.